Java

Overview

Instrumenting your Java and JVM-based applications to generate traces, logs, and metrics is a powerful way to gain deep insights into its behavior and performance. By adding instrumentation, you enable your application to emit valuable data that can be used for monitoring, troubleshooting, and optimization.

Dash0 supports automatic instrumentation of Java applications through OpenTelemetry's open-source and vendor-agnostic libraries.

Use Cases

• Understand outgoing and incoming HTTP requests through traces and metrics. Allowing drill-downs to the database level.
• You can see which database statements were executed and how long they took, which gives you valuable data to optimize your applications.
• Reveal (uncaught) errors and the context in which they happened.

Install

The OpenTelemetry Java SDK provides a ready-made auto-instrumentation agent that simplifies instrumentation:

wget https://github.com/open-telemetry/opentelemetry-java-instrumentation/releases/latest/download/opentelemetry-javaagent.jar

The opentelemetry-javaagent.jar file contains both the agent and instrumentation libraries, enabling automatic instrumentation of your JVM-based application without modifying its source code.

Configure

To send data to Dash0, configure the following settings:

1. Register the OpenTelemetry Java Agent
Ensure that the OpenTelemetry Java agent is registered when starting your application by using the -javaagent parameter:

java -javaagent:path/to/opentelemetry-javaagent.jar -jar myapp.jar

Alternatively, you can set an environment variable to automatically add the -javaagent parameter to the JVM:

export JAVA_TOOL_OPTIONS="-javaagent:path/to/opentelemetry-javaagent.jar"
java -jar myapp.jar

2. Specify the application service name:

export OTEL_SERVICE_NAME="my-first-observable-java-service"

Replace my-first-observable-java-service with a meaningful name that identifies your application.

3. Set up the data export endpoint and authorization token:

export OTEL_EXPORTER_OTLP_ENDPOINT="{{endpoint_otlp_http}}"
export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer {{token}}"

Note: You can specify which dataset to send data to by adding the Dash0-Dataset header. For example:

export OTEL_EXPORTER_OTLP_HEADERS="Authorization=Bearer {{token}},Dash0-Dataset={{dataset}}"

For more information, see the dataset documentation.

Kubernetes Setup

In case you are not using the Dash0 operator for Kubernetes to deploy your application, you should extend the OpenTelemetry resource attributes to include the Pod UID. This is important to merge the resources between logs,traces and metrics. You can do this by adding the following environment variables to your deployment:

env:
  - name: K8S_POD_UID
    valueFrom:
      fieldRef:
        apiVersion: v1
        fieldPath: metadata.uid
  - name: K8S_POD_NAME
    valueFrom:
      fieldRef:
        apiVersion: v1
        fieldPath: metadata.name
  - name: OTEL_RESOURCE_ATTRIBUTES
    value: k8s.pod.name=$(K8S_POD_NAME),k8s.pod.uid=$(K8S_POD_UID)

This will add the k8s.pod.name and k8s.pod.uid attributes to the OpenTelemetry resource attributes, which will be included in all telemetry data sent to Dash0. To read more about resource equality and merging, please refer to the Dash0 docs.

In order to learn more about the importance of resource attributes read the blog post OpenTelemetry resource attributes: Best practices for Kubernetes

Supported Libraries and Frameworks

To see which libraries are automatically instrumented, refer to the OpenTelemetry registry.